Different Representations of Fuzzy Vectors

Fuzzy vectors were introduced as a description of imprecise quantities whose uncertainty originates from vagueness, not from a probabilistic model. Support functions are a classical tool for representation and computation with compact convex sets. The combination of these two techniques--support functions of fuzzy vectors--has been proposed by Puri and Ralescu. Independently, Bobylev proposed another type of support functions which allows a more economical representation. However, the form of the functions is not very intuitive. We suggest a new type of support functions which combines the advantages of both preceding approaches. We characterize the functions which are support functions of fuzzy vectors in the new sense.

• Type: Conference
• Year: 2009
• Where: ECSQARU
• Authors: Jiuzhen Liang, Mirko Navara, Thomas Vetterlein
• Keywords: Automated Reasoning, Compact Convex Sets, ECSQARU 2009, Fuzzy Vectors, Support Functions